Engineering Lead (AI/ML Focus)

Protogon Research builds AI models with a deep understanding of the world, monetizing them through proprietary trading. Founded and led by serial entrepreneur Rafael Cosman—co-founder of Archblock and the TrueFi DeFi protocol—Protogon is charting a path toward superintelligence.

Why Trading?

Focusing on trading provides several key advantages:

• Proprietary models and datasets – This helps us avoid the race-to-the-bottom faced by many other AI companies.
• Fast innovation cycle – Technological advancements directly translate into increased revenue, allowing us to rapidly test and implement improvements.
• Pure focus on AI development – With no need for sales, marketing, or customer support, we can concentrate on building groundbreaking systems.
• True understanding, not imitation – We create AI that deeply understands the world, rather than just replicating human behavior or generating superficial outputs.

We believe trading is a powerful testbed for developing highly intelligent AI systems, offering unique advantages over other approaches. Backed by top VCs, our highly technical team is on a mission to build the most transformative invention of the 21st century.

Unlike traditional quant funds, our goal isn't to focus on short-term profits but to build the long-term success of our AI technology. While we leverage AI for trading, everything—from our investors to our culture—is aligned with this vision of lasting impact. Moreover, we're not just another AI company layering a thin wrapper over existing technologies or burning through resources on models that add little value. Our work is original, proprietary, and defensible.

We are a small, dynamic team of eight based in San Diego, CA, and we are seeking a talented Engineering Lead with a strong emphasis in AI and Machine Learning Engineering to help us build impactful technology and drive innovation. This role is central to our AI strategy: you will lead our MLE team, set the technical direction for our models and infrastructure, and own the end-to-end development of production AI systems. We work primarily in person and are looking for candidates based in or willing to relocate to the San Diego area.

Responsibilities and Expectations

This role is expected to be primarily hands-on, with the majority of time spent building, training, and deploying models, while providing leadership to the entire engineering team.

• Applied AI Execution & Modeling Leadership Own the design, development, and deployment of production ML models used in live trading environments. Work closely with leadership and engineering partners to improve predictive performance, robustness, and adaptability across changing market conditions, with a strong focus on practical implementation and measurable real-world impact.
• Technical Leadership & Collaboration Lead the entire engineering organization, overseeing both ML engineers and broader software engineers. Set technical direction across the team, combine hands-on AI/ML execution with engineering management, and own hiring, onboarding, and development of engineers in partnership with company leadership.
• AI Systems, Data Pipelines & Model Quality Contribute to and improve core ML infrastructure, including data pipelines, training workflows, evaluation tooling, and inference systems. Ensure models are reliable, observable, and performant in both training and production environments.
• Execution Against Trading Objectives Work directly with leadership to identify high-impact modeling opportunities and translate them into executable ML work. Operate in an early-stage environment where objectives may be loosely defined, validating approaches through rapid experimentation and integrating models into evolving systems.

Who You Are

• Experienced Applied ML Engineer: You bring 5–8 years of applied AI/ML experience, with 3+ years of engineering leadership experience, including managing full engineering teams (not just AI/ML). You have a strong track record of shipping ML systems to production in environments where model performance directly impacts outcomes.
• Execution-Focused Problem Solver: You excel at turning ambiguous problems into executable modeling work. You prioritize reliability, performance, and iteration over novelty, and communicate clearly with engineering, operations, and management.
• Strong Technical Foundation: You have hands-on experience with modern ML techniques (e.g., deep learning, sequence models, RL, or time-series modeling). You are fluent in Python and familiar with frameworks such as PyTorch, and have experience working with training pipelines, evaluation systems, and production ML infrastructure.
• Collaborative Technical Leader: You have a proven track record of leading engineering teams, not just AI/ML pods, but broader engineering organizations. Critically, this is a hands-on role: you expect to spend roughly 70% of your time writing code and building models, and 30% on management and leadership. You can set and execute on engineering-wide strategy, remain deeply involved in day-to-day technical work, and build a high-performing team culture around technical excellence.

Nice to Have:

• Experience applying ML in quantitative finance or trading
• PhD in AI/ML or similar research experience
• Experience improving ML platforms, data pipelines, or deployment workflows in production systems
• Strong collaboration with Portfolio Managers, traders, or domain experts to translate insights into modeling improvements

What We Offer:

• Competitive Compensation: A competitive base salary with equity ownership on top
• Comprehensive Benefits Package: Medical, dental, and vision coverage designed to support you and your family's well-being.
• Financial & Wellness Support: 401(k), Commuter, FSA, and HSA programs, and additional benefits to support long-term stability.
• Flexible Time Off & Work-Life Balance: Generous vacation, sick leave, and company holidays, with flexibility to recharge when needed.

Additional Information

• This role requires current authorization to work in the United States; Protogon Research is not able to provide visa sponsorship at this time.